toupiea

function Invariant_Line_Feature_Matching ___DESCRIPTION___ Compare segmented line pairs as 4 dimentional line pair features ( Q1 , Q2 , Drelative , D? ) Example : Invariant_Line_Feature_Matching ( ) ___REFERENCE___ Paper 1 : Line Feature Matching Technique Based on an Eigenvector Approach Park, Lee, Lee - Ideal - CV and Im. Und. - 77, 263-283 - (2000)( function Invariant_Line_Feature_Matching ___DESCRIPTION___ Compare segmented line pairs as 4 dimentional line pair features ( Q1 , Q2 , Drelative , D? ) Example : Invariant_Line_Feature_Matching ( ) ___REFERENCE___ Paper 1 : Line Feature Matching Technique Based on an Eigenvector Approach Park, Lee, Lee- Ideal- CV and Im. Und.- 77, 263-283- (2000))

说明：  我毕设时的MSK编程，，MATLAB，，带有差分编码的，程序比较简洁易懂(I completed the set when the MSK program,, MATLAB,, with differential coding, the procedure is simple and easy to understand)

Model order reduction using proper orthogonal decomposition (POD)

empirical formula with kaiser clc clear all fs=1000 fc=250 df=50 r=0.001 f=fc/fs dw=2*pi*(df/fs) a=-20*log(r) n=floor(((a-8)/(2.285*dw))+1) if a>50 b=0.1102*(a-8.7) elseif a>=21 && a<=50 b=0.5842*((a-21)^0.4)+0.07886*(a-21) elseif a<21 b=0.0 end w=kaiser(n,b) for i=1:n if i~=(n-1)/2 hd(i)= (2*f*sin((i-((n-1)/2))*2*pi*f))/((i-((n-1)/2))*2*pi*f) elseif i==(n-1)/2 hd(i)=2*f end end for j=1:n h(j)=w(j)*hd(j) end subplot(3,1,1), plot(w) subplot(3,1,2), plot(h) subplot(3,1,3), plot(h,n)

说明：  用于各种分类的支持向量机matlab程序，可自定训练集和验证集数量(lib-SVM matlab program)

MACD量化趋势交易的MATLAB编程，回测各指标的代码以及Excel输出(MACD quantify trends transaction MATLAB programming, backtesting of each index code, and Excel output)

对光伏电板进行详细建模，在simulink里面搭建，并进行最大功率跟踪(modeling PV，MPPT)

说明：  近年来，逆散射已经成为非常热门的话题，在这里我提交一个music算法的matlab例程，供大家参考。(In recent years, inverse scattering has become a very hot topic. Here I submit a matlab routine of music algorithm for your reference.)

该程序主要用来求解正弦分量的局部方差分维数，便于后续的模式识别方法的分类(The program is mainly used to solve the sinusoidal component of the partial differential side dimension, easy to follow the classification of the pattern recognition method)

说明：  此為用來計算特徵向量值以及特徵向量的程式(Eigenvalue and eigenvector calculate)